Difference between revisions of "SIR Modeling"


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<center><math>S_{t+1} = S_t - \beta S_t I_t</math></center>
 
<center><math>S_{t+1} = S_t - \beta S_t I_t</math></center>
 +
 +
<center><math>I_{t+1} = I_t + \beta S_t I_t - \gamma I_t</math></center>
 +
 +
<center><math>R_{t+1} = R_t + \gamma I_t</math></center>
  
 
where;
 
where;
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<math>S</math> number of susceptible individuals,
 
<math>S</math> number of susceptible individuals,
  
<math>I</math> number of infected individuals.
+
<math>I</math> number of infected individuals,
  
<center><math>I_{t+1} = I_t + \beta S_t I_t - \gamma I_t</math></center>
+
<math>R</math> number of recovered individuals,
 +
 
 +
<math>\beta</math> the average number of contacts per person per time,
  
<center><math>R_{t+1} = R_t + \gamma I_t</math></center>
+
<math>\gamma</math> the transition rate.

Revision as of 13:54, 2 April 2020

Compartmental Modeling

​Discrete-time SIR modeling of infections/recovery

The model consists of individuals who are either Susceptible ([math]S[/math]), Infected ([math]I[/math]), or Recovered ([math]R[/math]).

The epidemic proceeds via a growth and decline process. This is the core model of infectious disease spread and has been in use in epidemiology for many years.

The dynamics are given by the following 3 equations.

[math]S_{t+1} = S_t - \beta S_t I_t[/math]
[math]I_{t+1} = I_t + \beta S_t I_t - \gamma I_t[/math]
[math]R_{t+1} = R_t + \gamma I_t[/math]

where;

[math]S[/math] number of susceptible individuals,

[math]I[/math] number of infected individuals,

[math]R[/math] number of recovered individuals,

[math]\beta[/math] the average number of contacts per person per time,

[math]\gamma[/math] the transition rate.